2012 Data Release Notes

2012 R1 Release Notes December 18th, 2013

For 2012, there is a small change in the gravity model formulation. Tiny demands and supplies are now traded locally if possible. This will cause a slight bump to multipliers.

In the past we have made an effort to prevent negative labor income (ie, proprietor’s income losses exceeding employee compensation for a given sector). This year it was not possible for the farming sectors as it led to significant loss of those agricultural sectors for many counties. Negative labor income can lead to overall negative induced effects. Since this may not be logical for impact analysis, we suggest customizing an impact analysis by zeroing out negative proprietor income in the event window.

The BEA provides data on TOPI by GSP sector (81 of them), by state. Previous to the 2012 data year, we were only making use of the U.S.-level data, using U.S. ratios to estimate state-level data. In the 2012 Data Season, we improved our process of incorporating the state-level BEA TOPI data. As such, there may be some large changes in TOPI for some states in some sectors compared to previous years.

2012 R2 Release Notes

More current GSP data: Due to the government sequestration in the Fall of 2013, the latest Gross State Product (GSP) data were not released to the public; thus, the first release of the 2012 IMPLAN data used lagged GSP data. The 2012 R2 data incorporate the most current GSP data. This will affect OPI and TOPI.

Improved Redefinitions: The NIPA control totals for Government Gross Investment in structures (from table 3.9.5) and Private Fixed Investment in structures (from table 5.3.5) have already been redefined – that is, they include all activity related to the construction of structures, regardless of which industry performed that construction. Thus, when redefining the Output of each sector, while we still need to take construction activity out of the other sectors, we do not need to add that activity to the construction sectors (since their output figures for the construction sectors presumably already includes that activity). Thus, in the 2012 R2 IMPLAN data and all future IMPLAN data sets, we will no longer add the non-construction-sector construction output to the construction sectors. However, the other sectors’ Employment, EC, PI, OPI, and IBT will continue to be moved into the construction sectors because the data for these factors is not redefined.

New ERS process: For Output for the agricultural sectors, we have shifted from using sales data to production data multiplied by the average price for that commodity for that year. The reason for this change is that agricultural commodities are not always sold in the same year that they are produced, making revenues an imprecise measure of Output. The same can be said for other manufacturing sectors; however, we get the Output data for those sectors from the Anuual Survey of Manufactures, which includes data on net inventory changes, which allows us to separate sales from production for those sectors.

New ORNL Impedences: We use inter-county impedences (cost of transport indexes) from the Oak Ridge National Laboratory for use in our gravity model to estimate inter-county trade flows. For IMPLAN data sets 2007 – 2012 R1, we had been using the same original set of ORNL impedences. In 2013, we acquired updated impedences from ORNL which were incorporated in the 2012 R2 IMLAN data set.

New Zip-Code Population Data: It was pointed out to us by a customer that the Census Bureau showed a population of 33 for zip-code 18430, yet IMPLAN did not have a data set for that zip-code. We checked our raw 2010 Decennial Census data and did not see the zip-code there (so we did NOT make a mistake). However, a re-download of the 2010 Census Data DID have data for that zip-code – and 191 others! So we incorporated them into our list of unique zip-codes and they now show up in the new set of zip-code data files. The new Census data did not involve any changed values to zip-codes that were in the original download. In the process of ensuring that all zip-codes in a given county to sum to that county’s values, the other zip-codes in counties for which new zip-code data were created will experience a very slight decrease in their values.